• Perspectives in Nursing Science
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• 제8권2호
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• pp.121-128
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• 2011

Sensitive issues are both common and problematic for health care providers because sensitive issues may interfere with the future provider-client relationship and effective care. Most current training for providers focuses on a particular issue, but this is inadequate because many issues may be sensitive, and which issues will be sensitive is unpredictable. We argue that issues become sensitive when they activate one or more of three common triggers, fear, stigma, and taboo. A cycle of negative internal and interpersonal responses to the sensitive issue often leads to unresolved health issues for clients and stress and feelings of inadequacy for providers. We recommend integrated pre-service and in-service skill building to help individual health care providers respond appropriately to a wide variety of sensitive issues. We also identify specific policies and procedures to strengthen organizational support for caregivers so that providers can address these sensitive issues effectively with their clients.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.101-108
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• 2017

The study proposed a system that filters the data that is entered when analyzing big data such as SNS and BLOG. Personal information includes impersonal personal information, but there is also personal information that distinguishes it from personal information, such as religious institution, personal feelings, thoughts, or beliefs. Define these personally identifiable information as sensitive information. In order to prevent this, Article 23 of the Privacy Act has clauses on the collection and utilization of the information. The proposed system structure is divided into two stages, including Big Data Processing Processes and Sensitive Information Filtering Processes, and Big Data processing is analyzed and applied in Big Data collection in four stages. Big Data Processing Processes include data collection and storage, vocabulary analysis and parsing and semantics. Sensitive Information Filtering Processes includes sensitive information questionnaires, establishing sensitive information DB, qualifying information, filtering sensitive information, and reliability analysis. As a result, the number of Big Data performed in the experiment was carried out at 84.13%, until 7553 of 8978 was produced to create the Ontology Generation. There is considerable significan ce to the point that Performing a sensitive information cut phase was carried out by 98%.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.251-261
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• 2022

As AI has a wide range of influence on human social life, issues of transparency and ethics of AI are emerging. In particular, it is widely known that due to the existence of historical bias in data against ethics or regulatory frameworks for fairness, trained AI models based on such biased data could also impose bias or unfairness against a certain sensitive group (e.g., non-white, women). Demographic disparities due to AI, which refer to socially unacceptable bias that an AI model favors certain groups (e.g., white, men) over other groups (e.g., black, women), have been observed frequently in many applications of AI and many studies have been done recently to develop AI algorithms which remove or alleviate such demographic disparities in trained AI models. In this paper, we consider a problem of using the information in the sensitive variable for fair prediction when using the sensitive variable as a part of input variables is prohibitive by laws or regulations to avoid unfairness. As a way of reflecting the information in the sensitive variable to prediction, we consider a two-stage procedure. First, the sensitive variable is fully included in the learning phase to have a prediction model depending on the sensitive variable, and then an imputed sensitive variable is used in the prediction phase. The aim of this paper is to evaluate this procedure by analyzing several benchmark datasets. We illustrate that using an imputed sensitive variable is helpful to improve prediction accuracies without hampering the degree of fairness much.

• BMB Reports
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• 제31권4호
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• pp.405-408
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• 1998

Endonuclease-sensitive sites detected by T4 endonuclease V or UvrABC nuclease treatments were compared in the dihydrofolate reductase gene of UV-irradiated Chinese hamster ovary B-11 cells. The number of endonuclease-sensitive sites detected by T4 endonuclease V treatment followed by NaOH denaturation was twice that of formamide denaturation. Repeated treatment of damaged genomic DNA with T4 endonuclease V resulted in no further increase in the number of endonuclease-sensitive sites detected. The numbers of endonuclease-sensitive sites detected by UvrABC nuclease using each denaturation condition were similar. Sequential treatment with the two endonucleases using formamide denaturation resulted in twice the number of endonuclease-sensitive sites detected by treatment of each nuclease alone. Due to a lack of AP endonuclease activity these results suggest the presence of T4 endonuclease V-sensitive sites which could be complemented by alkaline gel separation or by UvrABC nuclease treatment.

• 전기전자학회논문지
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• 제5권1호
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• pp.43-51
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• 2001

메모리의 집적도가 올라갈수록 원치 않는 셀간의 간섭과 동시에 bit-line간의 상호 노이즈도 증가하게 된다. 그리고 높은 고장 검출율을 요구하는 고집적 메모리의 테스트는 많은 테스트 백터를 요구하게 되거나 비교적 큰 추가 테스트 회로를 요구하게 된다. 지금까지 기존의 테스트 알고리즘은 이웃 bit-line의 간섭이 아니라 이웃 셀에 중점을 두었다. 본 논문에서는 NPSFs(Neighborhood Pattern Sensitive Faults)를 기본으로 한 NBLSFs(Neighborhood Bit-Line Sensitive Faults)를 위한 새로운 테스터 알고리즘을 제안한다. 그리고 제안된 알고리즘은 부가 회로를 요구하지 않는다. 메모리 테스트를 위해 기존의 5개의 셀 레이아웃이나 9개의 셀 레이아웃을 사용하지 않고 NBLSF 검출에 최소한 크기인 3개의 셀 레이아웃을 이용하였다. 더구나 이웃 bit-line에 의한 최대의 상호잡음을 고려하기 위해 테스트 동작에 refresh 동작을 추가하였다(예 $write{\rightarrow}\;refresh{\rightarrow}\;read$). 또한 고착고장, 천이고장, 결합고장, 기존의 pattern sensitive 고장, 그리고 이웃 bit-line sensitive 고장 등도 검출될 수 있음을 보여준다.

• E2M - 전기 전자와 첨단 소재
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• 제10권4호
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• pp.349-354
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• 1997

This paper aims at studying the improvement of test method for t-weight sensitive fault (t-wsf) detect. The development of RAM fabrication technology results in not only the increase at device density on chips but also the decrease in line widths in VLSI. But, the chip size that was large and complex is shortened and simplified while the cost of chips remains at the present level, in many cases, even lowering. First of all, The testing patterns for RAM fault detect, which is apt to be complicated , need to be simplified. This new testing method made use of Local Lower Bound (L.L.B) which has the memory with the beginning pattern of 0(l) and the finishing pattern of 0(1). The proposed testing patterns can detect all of RAM faults which contain stuck-at faults, coupling faults. The number of operation is 6N at 1-weight sensitive fault, 9,5N at 2-weight sensitive fault, 7N at 3-weight sensitive fault, and 3N at 4-weight sensitive fault. This test techniques can reduce the number of test pattern in memory cells, saving much more time in test, This testing patterns can detect all static weight sensitive faults and pattern sensitive faults in RAM.

• 한국음향학회지
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• 제19권8호
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• pp.3-11
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• 2000

음성의 특성은 지연에 매우 민감한 (delay-sensitive) 트래픽으로 시스템에서 손실에 민감한 (loss-sensitive) 다른 트래픽과 동일한 방식으로 서비스되어서는 두 트래픽 모두의 QoS (Quality of Service)를 만족시킬 수 없다. 효율적인 트래픽의 처리를 위해서는 시스템의 상태에 따라 손실에 민감한 트래픽에 영향을 적게 주면서 지연민감 트래픽의 성능도 만족하는 것이 바람직하다. 본 논문에서 도입한 동적우선권제어함수 (Dynamic Priority Control Function, DPCF)는 시스템의 상태에 따라 각 트래픽에 우선권을 동적으로 할당하여 서비스 스케줄링을 제어하는 함수f(·)로 기존의 우선권 제어방식을 더욱 일반화시킨 방식이다. 클래스 1의 손실민감 트래픽과 음성과 같은 클래스 2의 지연민감 트래픽을 수용하는 시스템에 TBPJ (Threshold-based Bernoulli Priority Jump) 방식의 DPCF을 적용하여 성능을 분석하였다. DPCF은 각 시스템에 대기하고 있는 트래픽의 양과 시스템의 가용 용량인 버퍼의 threshold에 따라 각 트래픽 클래스에 우선권을 동적으로 할당하여 서비스가 이루어지도록 한다. 성능분석을 통하여 TBPJ 제어방식이 기존의 우선권 제어 방식보다 성능 및 효율성에 있어서 우수함을 입증하였다. 즉 성능을 분석한 결과 손실민감 트래픽의 성능저하는 미미하고 지연민감 트래픽의 성능향상은 현저히 개선된 것을 확인하였다.

• Journal of Computing Science and Engineering
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• 제1권1호
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• pp.74-94
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• 2007

Nowadays, sharing data among organizations is often required during the business collaboration. Data mining technology has enabled efficient extraction of knowledge from large databases. This, however, increases risks of disclosing the sensitive knowledge when the database is released to other parties. To address this privacy issue, one may sanitize the original database so that the sensitive knowledge is hidden. The challenge is to minimize the side effect on the quality of the sanitized database so that non-sensitive knowledge can still be mined. In this paper, we study such a problem in the context of hiding sensitive frequent itemsets by judiciously modifying the transactions in the database. Unlike previous work, we consider the quality of the sanitized database especially on preserving the non-sensitive frequent itemsets. To preserve the non-sensitive frequent itemsets, we propose a border-based approach to efficiently evaluate the impact of any modification to the database during the hiding process. The quality of database can be well maintained by greedily selecting the modifications with minimal side effect. Experiments results are also reported to show the effectiveness of the proposed approach.

• Geomechanics and Engineering
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• 제16권5호
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• pp.513-525
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• 2018

Slope stability of sensitive clayey soils is particularly important when subjected to strength loss and deformation. Except for progressive failure, for most sensitive and insensitive slopes, it is important to review the feasibility of conventional analysis methods based on peak strength since peak strength governs slope stability before yielding. In this study, as a part of efforts to understand the behavior of sensitive clay slopes, a total of 12 centrifuge tests were performed for artificially sensitive and insensitive clay slopes using San Francisco Bay Mud (PI = 50) and Yolo Loam (PI = 10). In terms of slope stability, the results were analyzed using the updated instability factor ($N_I$). $N_I$ using equivalent unit weight to cause a failure is in reasonable agreement shown in the Taylor's chart ($N_I$ ~ 5.5). In terms of dynamic deformation, it is shown that two-way sliding is a more accurate approach than conventional one-way sliding. Two-way sliding may relate to diffused shear surfaces. The outcome of this study is contributable to analyzing stability and deformation of steep sensitive clay slopes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권4호
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• pp.300-307
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• 2012

When the volume of data grows big, some simple tasks could become a significant concern. Nearest neighbor search is such a task which finds from a data set the k nearest data points to queries. Locality-sensitive hashing techniques have been developed for approximate but fast nearest neighbor search. This paper introduces the notion of locality-sensitive hashing and surveys the locality-sensitive hashing techniques. It categories them based on several criteria, presents their characteristics, and compares their performance.